Imperial College London

ProfessorDanCrisan

Faculty of Natural SciencesDepartment of Mathematics

Professor of Mathematics
 
 
 
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Contact

 

+44 (0)20 7594 8489d.crisan Website

 
 
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Location

 

670Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inbook{Crisan:2022:10.1007/978-3-030-98519-6_4,
author = {Crisan, D and Lobbe, A and Ortiz-Latorre, S},
booktitle = {Stochastic Analysis, Filtering, and Stochastic Optimization: A Commemorative Volume to Honor Mark H. A. Davis's Contributions},
doi = {10.1007/978-3-030-98519-6_4},
pages = {79--100},
title = {Pathwise Approximations for the Solution of the Non-Linear Filtering Problem},
url = {http://dx.doi.org/10.1007/978-3-030-98519-6_4},
year = {2022}
}

RIS format (EndNote, RefMan)

TY  - CHAP
AB - We consider high order approximations of the solution of the stochastic filtering problem, derive their pathwise representation in the spirit of the earlier work of Clark [2] and Davis [10, 11] and prove their robustness property. In particular, we show that the high order discretised filtering functionals can be represented by Lipschitz continuous functions defined on the observation path space. This property is important from the practical point of view as it is in fact the pathwise version of the filtering functional that is sought in numerical applications. Moreover, the pathwise viewpointwill be a stepping stone into the rigorous development ofmachine learning methods for the filtering problem. This work is a cotinuation of [5] where a discretisation of the solution of the filtering problem of arbitrary order has been established. We expand the work in [5] by showing that robust approximations can be derived from the discretisations therein.
AU - Crisan,D
AU - Lobbe,A
AU - Ortiz-Latorre,S
DO - 10.1007/978-3-030-98519-6_4
EP - 100
PY - 2022///
SN - 9783030985189
SP - 79
TI - Pathwise Approximations for the Solution of the Non-Linear Filtering Problem
T1 - Stochastic Analysis, Filtering, and Stochastic Optimization: A Commemorative Volume to Honor Mark H. A. Davis's Contributions
UR - http://dx.doi.org/10.1007/978-3-030-98519-6_4
ER -